Genome Profiling of SARS-CoV-2 in Indonesia, ASEAN and the Neighbouring East Asian Countries: Features, Challenges and Achievements

Whole-Genome Sequencing and Mutation Analyses of SARS-CoV-2 Isolates from Indonesia

The SARS-CoV-2 infection that caused the COVID-19 pandemic has become a significant public health concern. New variants with distinct mutations have emerged, potentially impacting its infectivity, immune evasion capacity, and vaccine response. A whole-genome sequencing study of 292 SARS-CoV-2 isolates collected from selected regions of Indonesia between January and October 2021 was performed to identify the distribution of SARS-CoV-2 variants and common mutations in Indonesia. During January-April 2021, Indonesian lineages B.1.466.2 and B.1.470 dominated, but from May 2021, Delta's AY.23 lineage outcompeted them. An analysis of 7515 published sequences from January 2021 to June 2022 revealed a decline in Delta in November 2021, followed by the emergence of Omicron variants in December 2021. We identified C241T (5'UTR), P314L (NSP12b), F106F (NSP3), and D614G (Spike) mutations in all sequences. The other common substitutions included P681R (76.4%) and T478K (60%) in Spike, D377Y in Nucleocapsid (61%), and I82T in Membrane (60%) proteins. Breakthrough infection and prolonged viral shedding cases were associated with Delta variants carrying the Spike T19R, G142D, L452R, T478K, D614G, P681R, D950N, and V1264L mutations. The dynamic of SARS-CoV-2 variants in Indonesia highlights the importance of continuous genomic surveillance in monitoring and identifying potential strains leading to disease outbreaks.

SARS-CoV-2 lineages circulating during the first wave of the pandemic in North Sumatra, Indonesia

Objectives

To determine the lineage distribution of the virus during the first wave of the pandemic in North Sumatra, Indonesia.

Methods

A total of 20 samples with positive results based on reverse transcription-polymerase chain reaction were selected for virus culture and then performed whole-genome sequence analysis using next-generation sequencing which was applied by the Illumina MiSeq instrument.

Results

Whole-genome sequence analysis revealed that the majority of our samples belong to lineages B.1.468 (n = 10), B.1 (n = 5), B.1.1 (n = 2), B.1.1.398 (n = 2), and B.6 (n = 1). Other unique amino acid mutations found in our samples were present in A58T on non-structural protein (NSP3) (70%), P323L on NSP12 (95%), Q57H on NS3 protein (75%), and D614G on S (100%).

Conclusion

The SARS-CoV-2 lineage B.1.468 may be the main virus variant circulating in North Sumatra at the beginning of the emergence of COVID-19 cases in this province.

Timeline of SARS-CoV-2 Transmission in Sabah, Malaysia: Tracking the Molecular Evolution

BACKGROUND

The COVID-19 pandemic poses an unprecedented public health challenge in Malaysia. The impact of COVID-19 varies between countries, including geographically divided states within a country. The deadly transmission of COVID-19 has taken a heavy toll in Sabah, Malaysia's third most populous state, contributing nearly 10% to the recorded national death toll as of 31 December 2022. Although several SARS-CoV-2 genome sequences have been analysed in Malaysia, molecular epidemiology data from Sabah focusing on the diversity and evolution of SARS-CoV-2 variants are still lacking. This study examines the major SARS-CoV-2 variants and emerging mutations from Sabah, the Malaysian Borneo, which is geographically divided from West Malaysia by the South China Sea.

METHODS

A total of 583 COVID-19 samples were subjected to whole genome sequencing and analysed with an additional 1123 Sabah COVID-19 sequences retrieved from the GISAID EpiCoV consortium. Nextclade and Pangolin were used to classify these sequences according to the clades and lineages. To determine the molecular evolutionary characteristics, Bayesian time-scaled phylogenetic analysis employing the maximum likelihood algorithm was performed on selected SARS-CoV-2 genome sequences, using the Wuhan-Hu-1 sequence as a reference.

RESULTS

Sabah was affected starting from the second COVID-19 wave in Malaysia, and the early sequences were classified under the O clade. The clade was gradually replaced during subsequent waves by G, GH, GK and GRA, with the latter being dominant as of December 2022. Phylogenetically, the Delta isolates in this study belong to the three main subclades 21A, 21J and 21I, while Omicron isolates belong to 21M, 21L and 22B. The time-scaled phylogeny suggested that SARS-CoV-2 introduced into Sabah originated from Peninsular Malaysia in early March 2020, and phylodynamic analysis indicated that increased viral spread was observed in early March and declined in late April, followed by an evolutionary stationary phase in June 2020.

CONCLUSION

Continuous molecular epidemiology of SARS-CoV-2 in Sabah will provide a deeper understanding of the emergence and dominance of each variant in the locality, thus facilitating public health intervention measures.

Toward a global virus genomic surveillance network

The COVID-19 pandemic galvanized the field of virus genomic surveillance, demonstrating its utility for public health. Now, we must harness the momentum that led to increased infrastructure, training, and political will to build a sustainable global genomic surveillance network for other epidemic and endemic viruses. We suggest a generalizable modular sequencing framework wherein users can easily switch between virus targets to maximize cost-effectiveness and maintain readiness for new threats. We also highlight challenges associated with genomic surveillance and when global inequalities persist. We propose solutions to mitigate some of these issues, including training and multilateral partnerships. Exploring alternatives to clinical sequencing can also reduce the cost of surveillance programs. Finally, we discuss how establishing genomic surveillance would aid control programs and potentially provide a warning system for outbreaks, using a global respiratory virus (RSV), an arbovirus (dengue virus), and a regional zoonotic virus (Lassa virus) as examples.

COVID-19 Vaccination and Clinical Outcomes at a Secondary Referral Hospital During the Delta Variant-dominant Period in West Sumatra, Indonesia

OBJECTIVES

The second wave of coronavirus disease 2019 (COVID-19) cases in Indonesia, during which the Delta variant predominated, took place after a vaccination program had been initiated in the country. This study was conducted to assess the impact of COVID-19 vaccination on unfavorable clinical outcomes including hospitalization, severe COVID-19, intensive care unit (ICU) admission, and death using a real-world model.

METHODS

This single-center retrospective cohort study involved patients with COVID-19 aged ≥18 years who presented to the COVID-19 emergency room at a secondary referral teaching hospital between June 1, 2021 and August 31, 2021. We used a binary logistic regression model to assess the effect of COVID-19 vaccination on unfavorable clinical outcomes, with age, sex, and comorbidities as confounding variables.

RESULTS

A total of 716 patients were included, 32.1% of whom were vaccinated. The elderly participants (≥65 years) had the lowest vaccine coverage among age groups. Vaccination had an effectiveness of 50% (95% confidence interval [CI], 25 to 66) for preventing hospitalization, 97% (95% CI, 77 to 99) for preventing severe COVID-19, 95% (95% CI, 56 to 99) for preventing ICU admission, and 90% (95% CI, 22 to 99) for preventing death. Interestingly, patients with type 2 diabetes had a 2-fold to 4-fold elevated risk of unfavorable outcomes.

CONCLUSIONS

Among adults, COVID-19 vaccination has a moderate preventive impact on hospitalization but a high preventive impact on severe COVID-19, ICU admission, and death. The authors suggest that relevant parties increase COVID-19 vaccination coverage, especially in the elderly population.

Sequence analysis of SARS-CoV-2 Delta variant isolated from Makassar, South Sulawesi, Indonesia

Introduction

This study aimed to perform mutation and phylogenetic analyses of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Delta variants and analyze the characteristic signs and symptoms of patients infected with SARS-CoV-2 Delta variant originated from Makassar during the Delta outbreak.Methods: We collected samples from patients who were infected with coronavirus disease 2019 (COVID-19) between June and October 2021. We selected the Quantitative Reverse Transcription-Polymerase Chain Reaction (PCR)-positive samples with a cycle threshold value of <30 for whole genome sequencing. Total viral ribonucleic acid (RNA) was isolated from 34 PCR-positive nasopharyngeal swab samples, and whole genome sequencing was performed using the Oxford Nanopore GridlON sequencer. Phylogenetic and maximum clade credibility analyses were performed using the Bayesian Markov chain Monte Carlo method.

Results

It was found that 33 patients were infected with the SARS-CoV-2 Delta variant in this cohort study, among whom 63.6% (21) patients were female. According to the clinical data, 24 (72.7%), 7 (21.2%), and 2 (6.1%) patients had mild, moderate, and severe COVID-19 infections. Phylogenetic analysis based on the spike and RNA-dependent RNA polymerase (RdRp) genes showed that the collected samples were clustered in the main lineage of B.1.617.2 (Delta variant). The Delta variants had a high frequency of distinct mutations in the spike protein region, including T19R (94.12%), L452R (88.23%), T478K (91.17%), D614G (97%), P681R (97%), and D950 N (97%). Other unique mutations found in a smaller frequency in our samples were present in the N-terminal domain, including A27T (2.94%) and A222V (14.70%), and in the receptor-binding domain, including Q414K (5.88%), G446V (2.94%), and T470 N (2.94%).

Conclusion

This study revealed the unique mutations in the S protein region of Delta variants. T19R, L452R, T478K/T478R, D614G, P681R, and D950 N were the most common substitutions in Makassar's Delta variant.

SARS-CoV-2 genomic surveillance in Malaysia: displacement of B.1.617.2 with AY lineages as the dominant Delta variants and the introduction of Omicron during the fourth epidemic wave

OBJECTIVES

This study reported SARS-CoV-2 whole genome sequencing results from June 2021 to January 2022 from seven genome sequencing centers in Malaysia as part of the national surveillance program.

METHODS

COVID-19 samples that tested positive by reverse transcription polymerase chain reaction and with cycle threshold values <30 were obtained throughout Malaysia. Sequencing of SARS-CoV-2 complete genomes was performed using Illumina, Oxford Nanopore, or Ion Torrent platforms. A total of 6163 SARS-CoV-2 complete genome sequences were generated over the surveillance period. All sequences were submitted to the Global Initiative on Sharing All Influenza Data database.

RESULTS

From June 2021 to January 2022, Malaysia experienced the fourth wave of COVID-19 dominated by the Delta variant of concern, including the original B.1.617.2 lineage and descendant AY lineages. The B.1.617.2 lineage was identified as the early dominant circulating strain throughout the country but over time, was displaced by AY.59 and AY.79 lineages in Peninsular (west) Malaysia, and the AY.23 lineage in east Malaysia. In December 2021, pilgrims returning from Saudi Arabia facilitated the introduction and spread of the BA.1 lineage (Omicron variant of concern) in the country.

CONCLUSION

The changing trends of circulating SARS-CoV-2 lineages were identified, with differences observed between west and east Malaysia. This initiative highlighted the importance of leveraging research expertise in the country to facilitate pandemic response and preparedness.

A Comparison of Bioinformatics Pipelines for Enrichment Illumina Next Generation Sequencing Systems in Detecting SARS-CoV-2 Virus Strains

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a newly emerging virus well known as the major cause of the worldwide pandemic due to Coronavirus Disease 2019 (COVID-19). Major breakthroughs in the Next Generation Sequencing (NGS) field were elucidated following the first release of a full-length SARS-CoV-2 genome on the 10 January 2020, with the hope of turning the table against the worsening pandemic situation. Previous studies in respiratory virus characterization require mapping of raw sequences to the human genome in the downstream bioinformatics pipeline as part of metagenomic principles. Illumina, as the major player in the NGS arena, took action by releasing guidelines for improved enrichment kits called the Respiratory Virus Oligo Panel (RVOP) based on a hybridization capture method capable of capturing targeted respiratory viruses, including SARS-CoV-2; therefore, allowing a direct map of raw sequences data to SARS-CoV-2 genome in downstream bioinformatics pipeline. Consequently, two bioinformatics pipelines emerged with no previous studies benchmarking the pipelines. This study focuses on gaining insight and understanding of target enrichment workflow by Illumina through the utilization of different bioinformatics pipelines named as 'Fast Pipeline' and 'Normal Pipeline' to SARS-CoV-2 strains isolated from Yogyakarta and Central Java, Indonesia. Overall, both pipelines work well in the characterization of SARS-CoV-2 samples, including in the identification of major studied nucleotide substitutions and amino acid mutations. A higher number of reads mapped to the SARS-CoV-2 genome in Fast Pipeline and merely were discovered as a contributing factor in a higher number of coverage depth and identified variations (SNPs, insertion, and deletion). Fast Pipeline ultimately works well in a situation where time is a critical factor. On the other hand, Normal Pipeline would require a longer time as it mapped reads to the human genome. Certain limitations were identified in terms of pipeline algorithm, whereas it is highly recommended in future studies to design a pipeline in an integrated framework, for instance, by using NextFlow, a workflow framework to combine all scripts into one fully integrated pipeline.

Tracking the molecular evolution and transmission patterns of SARS-CoV-2 lineage B.1.466.2 in Indonesia based on genomic surveillance data

Background

As a new epi-center of COVID-19 in Asia and a densely populated developing country, Indonesia is facing unprecedented challenges in public health. SARS-CoV-2 lineage B.1.466.2 was reported to be an indigenous dominant strain in Indonesia (once second only to the Delta variant). However, it remains unclear how this variant evolved and spread within such an archipelagic nation.

Methods

For statistical description, the spatiotemporal distributions of the B.1.466.2 variant were plotted using the publicly accessible metadata in GISAID. A total of 1302 complete genome sequences of Indonesian B.1.466.2 strains with high coverage were downloaded from the GISAID’s EpiCoV database on 28 August 2021. To determine the molecular evolutionary characteristics, we performed a time-scaled phylogenetic analysis using the maximum likelihood algorithm and called the single nucleotide variants taking the Wuhan-Hu-1 sequence as reference. To investigate the spatiotemporal transmission patterns, we estimated two dynamic parameters (effective population size and effective reproduction number) and reconstructed the phylogeography among different islands.

Results

As of the end of August 2021, nearly 85% of the global SARS-CoV-2 lineage B.1.466.2 sequences (including the first one) were obtained from Indonesia. This variant was estimated to account for over 50% of Indonesia’s daily infections during the period of March–May 2021. The time-scaled phylogeny suggested that SARS-CoV-2 lineage B.1.466.2 circulating in Indonesia might have originated from Java Island in mid-June 2020 and had evolved into two disproportional and distinct sub-lineages. High-frequency non-synonymous mutations were mostly found in the spike and NSP3; the S-D614G/N439K/P681R co-mutations were identified in its larger sub-lineage. The demographic history was inferred to have experienced four phases, with an exponential growth from October 2020 to February 2021. The effective reproduction number was estimated to have reached its peak (11.18) in late December 2020 and dropped to be less than one after early May 2021. The relevant phylogeography showed that Java and Sumatra might successively act as epi-centers and form a stable transmission loop. Additionally, several long-distance transmission links across seas were revealed.

Conclusions

SARS-CoV-2 variants circulating in the tropical archipelago may follow unique patterns of evolution and transmission. Continuous, extensive and targeted genomic surveillance is essential.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-022-01830-1.

Genomic Characterisation Reveals a Dominant Lineage of SARS-CoV-2 in Papua New Guinea

The coronavirus disease pandemic has highlighted the utility of pathogen genomics as a key part of comprehensive public health response to emerging infectious diseases threats, however, the ability to generate, analyse, and respond to pathogen genomic data varies around the world. Papua New Guinea (PNG), which has limited in-country capacity for genomics, has experienced significant outbreaks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with initial genomics data indicating a large proportion of cases were from lineages that are not well defined within the current nomenclature. Through a partnership between in-country public health agencies and academic organisations, industry, and a public health genomics reference laboratory in Australia a system for routine SARS-CoV-2 genomics from PNG was established. Here we aim to characterise and describe the genomics of PNG’s second wave and examine the sudden expansion of a lineage that is not well defined but very prevalent in the Western Pacific region. We generated 1797 sequences from cases in PNG and performed phylogenetic and phylodynamic analyses to examine the outbreak and characterise the circulating lineages and clusters present. Our results reveal the rapid expansion of the B.1.466.2 and related lineages within PNG, from multiple introductions into the country. We also highlight the difficulties that unstable lineage assignment causes when using genomics to assist with rapid cluster definitions.